cjwbw / blipdiffusion-controlnet

prompt: on a marble table
style_image
guidance_scale: 7.5
controlnet_type: canny
negative_prompt: over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry
condtioning_image
num_inference_steps: 50
style_subject_category: flower
target_subject_category: bag

{
  "prompt": "on a marble table",
  "style_image": "https://replicate.delivery/pbxt/KNcAs3AO0VstO21vQLg2qmmkzM11Rp6KiSpEw7OjhOOTutuA/flower.jpg",
  "guidance_scale": 7.5,
  "controlnet_type": "canny",
  "negative_prompt": "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
  "condtioning_image": "https://replicate.delivery/pbxt/KNcAs1cHqRYVeehwZbqcxuKRXQjr2pdm7OL8Hhp11JfIhmHk/bag.png",
  "num_inference_steps": 50,
  "style_subject_category": "flower",
  "target_subject_category": "bag"
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run cjwbw/blipdiffusion-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cjwbw/blipdiffusion-controlnet:0072c227cdc7eea6c41411b54655b874faac1a7b8288386dc2a3c677c6faa403",
  {
    input: {
      prompt: "on a marble table",
      style_image: "https://replicate.delivery/pbxt/KNcAs3AO0VstO21vQLg2qmmkzM11Rp6KiSpEw7OjhOOTutuA/flower.jpg",
      guidance_scale: 7.5,
      controlnet_type: "canny",
      negative_prompt: "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
      condtioning_image: "https://replicate.delivery/pbxt/KNcAs1cHqRYVeehwZbqcxuKRXQjr2pdm7OL8Hhp11JfIhmHk/bag.png",
      num_inference_steps: 50,
      style_subject_category: "flower",
      target_subject_category: "bag"
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run cjwbw/blipdiffusion-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cjwbw/blipdiffusion-controlnet:0072c227cdc7eea6c41411b54655b874faac1a7b8288386dc2a3c677c6faa403",
    input={
        "prompt": "on a marble table",
        "style_image": "https://replicate.delivery/pbxt/KNcAs3AO0VstO21vQLg2qmmkzM11Rp6KiSpEw7OjhOOTutuA/flower.jpg",
        "guidance_scale": 7.5,
        "controlnet_type": "canny",
        "negative_prompt": "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
        "condtioning_image": "https://replicate.delivery/pbxt/KNcAs1cHqRYVeehwZbqcxuKRXQjr2pdm7OL8Hhp11JfIhmHk/bag.png",
        "num_inference_steps": 50,
        "style_subject_category": "flower",
        "target_subject_category": "bag"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

To learn more, take a look at the guide on getting started with Python.

Run cjwbw/blipdiffusion-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "cjwbw/blipdiffusion-controlnet:0072c227cdc7eea6c41411b54655b874faac1a7b8288386dc2a3c677c6faa403",
    "input": {
      "prompt": "on a marble table",
      "style_image": "https://replicate.delivery/pbxt/KNcAs3AO0VstO21vQLg2qmmkzM11Rp6KiSpEw7OjhOOTutuA/flower.jpg",
      "guidance_scale": 7.5,
      "controlnet_type": "canny",
      "negative_prompt": "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
      "condtioning_image": "https://replicate.delivery/pbxt/KNcAs1cHqRYVeehwZbqcxuKRXQjr2pdm7OL8Hhp11JfIhmHk/bag.png",
      "num_inference_steps": 50,
      "style_subject_category": "flower",
      "target_subject_category": "bag"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2024-02-10T15:11:23.295152Z",
  "created_at": "2024-02-10T15:11:18.635671Z",
  "data_removed": false,
  "error": null,
  "id": "sciics3b3jf7xgfs6k5ur35vli",
  "input": {
    "prompt": "on a marble table",
    "style_image": "https://replicate.delivery/pbxt/KNcAs3AO0VstO21vQLg2qmmkzM11Rp6KiSpEw7OjhOOTutuA/flower.jpg",
    "guidance_scale": 7.5,
    "controlnet_type": "canny",
    "negative_prompt": "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
    "condtioning_image": "https://replicate.delivery/pbxt/KNcAs1cHqRYVeehwZbqcxuKRXQjr2pdm7OL8Hhp11JfIhmHk/bag.png",
    "num_inference_steps": 50,
    "style_subject_category": "flower",
    "target_subject_category": "bag"
  },
  "logs": "Using seed: 7071\n  0%|          | 0/51 [00:00<?, ?it/s]\n  4%|▍         | 2/51 [00:00<00:02, 19.83it/s]\n  8%|▊         | 4/51 [00:00<00:02, 18.21it/s]\n 12%|█▏        | 6/51 [00:00<00:02, 17.77it/s]\n 16%|█▌        | 8/51 [00:00<00:02, 17.56it/s]\n 20%|█▉        | 10/51 [00:00<00:02, 17.39it/s]\n 24%|██▎       | 12/51 [00:00<00:02, 17.31it/s]\n 27%|██▋       | 14/51 [00:00<00:02, 16.96it/s]\n 31%|███▏      | 16/51 [00:00<00:02, 16.84it/s]\n 35%|███▌      | 18/51 [00:01<00:01, 16.73it/s]\n 39%|███▉      | 20/51 [00:01<00:01, 16.95it/s]\n 43%|████▎     | 22/51 [00:01<00:01, 17.07it/s]\n 47%|████▋     | 24/51 [00:01<00:01, 17.08it/s]\n 51%|█████     | 26/51 [00:01<00:01, 17.11it/s]\n 55%|█████▍    | 28/51 [00:01<00:01, 17.15it/s]\n 59%|█████▉    | 30/51 [00:01<00:01, 17.15it/s]\n 63%|██████▎   | 32/51 [00:01<00:01, 17.10it/s]\n 67%|██████▋   | 34/51 [00:01<00:01, 16.75it/s]\n 71%|███████   | 36/51 [00:02<00:00, 17.03it/s]\n 75%|███████▍  | 38/51 [00:02<00:00, 17.11it/s]\n 78%|███████▊  | 40/51 [00:02<00:00, 17.17it/s]\n 82%|████████▏ | 42/51 [00:02<00:00, 17.12it/s]\n 86%|████████▋ | 44/51 [00:02<00:00, 17.19it/s]\n 90%|█████████ | 46/51 [00:02<00:00, 17.16it/s]\n 94%|█████████▍| 48/51 [00:02<00:00, 17.15it/s]\n 98%|█████████▊| 50/51 [00:02<00:00, 17.12it/s]\n100%|██████████| 51/51 [00:02<00:00, 17.16it/s]",
  "metrics": {
    "predict_time": 4.621828,
    "total_time": 4.659481
  },
  "output": "https://replicate.delivery/pbxt/goow5E14vb6TABDkcGBXMeCBKPZ5j14EAtBMpHjtT6XNIqKJA/out.png",
  "started_at": "2024-02-10T15:11:18.673324Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/sciics3b3jf7xgfs6k5ur35vli",
    "cancel": "https://api.replicate.com/v1/predictions/sciics3b3jf7xgfs6k5ur35vli/cancel"
  },
  "version": "0072c227cdc7eea6c41411b54655b874faac1a7b8288386dc2a3c677c6faa403"
}

Generated in

4.6 seconds

Tweak it Share Report

Prediction

cjwbw/blipdiffusion-controlnet:0072c227cdc7eea6c41411b54655b874faac1a7b8288386dc2a3c677c6faa403

Model

cjwbw/blipdiffusion-controlnet:0072c227

rkqcqjlb5yfzubsedohlvv5jmi

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

3.1s

Created

over 1 year ago

Input

seed: 10
prompt: on a marble table
style_image
guidance_scale: 7.5
controlnet_type: canny
negative_prompt: over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry
condtioning_image
num_inference_steps: 25
style_subject_category: flower
target_subject_category: teapot

{
  "seed": 10,
  "prompt": "on a marble table",
  "style_image": "https://replicate.delivery/pbxt/KNc7eIC5UqBH5GxAUu3i5WWgQooBWg1WQmKlZyFczvaftVw5/flower.jpg",
  "guidance_scale": 7.5,
  "controlnet_type": "canny",
  "negative_prompt": "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
  "condtioning_image": "https://replicate.delivery/pbxt/KNc7dtQmRYksrDn4eC1qGrtlBJIkHHmk4S7OSMT8UAYMHRul/kettle.jpg",
  "num_inference_steps": 25,
  "style_subject_category": "flower",
  "target_subject_category": "teapot"
}

Install Replicate’s Node.js client library:

npm install replicate

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run cjwbw/blipdiffusion-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cjwbw/blipdiffusion-controlnet:0072c227cdc7eea6c41411b54655b874faac1a7b8288386dc2a3c677c6faa403",
  {
    input: {
      seed: 10,
      prompt: "on a marble table",
      style_image: "https://replicate.delivery/pbxt/KNc7eIC5UqBH5GxAUu3i5WWgQooBWg1WQmKlZyFczvaftVw5/flower.jpg",
      guidance_scale: 7.5,
      controlnet_type: "canny",
      negative_prompt: "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
      condtioning_image: "https://replicate.delivery/pbxt/KNc7dtQmRYksrDn4eC1qGrtlBJIkHHmk4S7OSMT8UAYMHRul/kettle.jpg",
      num_inference_steps: 25,
      style_subject_category: "flower",
      target_subject_category: "teapot"
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Import the client:

import replicate

Run cjwbw/blipdiffusion-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cjwbw/blipdiffusion-controlnet:0072c227cdc7eea6c41411b54655b874faac1a7b8288386dc2a3c677c6faa403",
    input={
        "seed": 10,
        "prompt": "on a marble table",
        "style_image": "https://replicate.delivery/pbxt/KNc7eIC5UqBH5GxAUu3i5WWgQooBWg1WQmKlZyFczvaftVw5/flower.jpg",
        "guidance_scale": 7.5,
        "controlnet_type": "canny",
        "negative_prompt": "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
        "condtioning_image": "https://replicate.delivery/pbxt/KNc7dtQmRYksrDn4eC1qGrtlBJIkHHmk4S7OSMT8UAYMHRul/kettle.jpg",
        "num_inference_steps": 25,
        "style_subject_category": "flower",
        "target_subject_category": "teapot"
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

To learn more, take a look at the guide on getting started with Python.

Run cjwbw/blipdiffusion-controlnet using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "cjwbw/blipdiffusion-controlnet:0072c227cdc7eea6c41411b54655b874faac1a7b8288386dc2a3c677c6faa403",
    "input": {
      "seed": 10,
      "prompt": "on a marble table",
      "style_image": "https://replicate.delivery/pbxt/KNc7eIC5UqBH5GxAUu3i5WWgQooBWg1WQmKlZyFczvaftVw5/flower.jpg",
      "guidance_scale": 7.5,
      "controlnet_type": "canny",
      "negative_prompt": "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
      "condtioning_image": "https://replicate.delivery/pbxt/KNc7dtQmRYksrDn4eC1qGrtlBJIkHHmk4S7OSMT8UAYMHRul/kettle.jpg",
      "num_inference_steps": 25,
      "style_subject_category": "flower",
      "target_subject_category": "teapot"
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

{
  "completed_at": "2024-02-10T15:17:38.288945Z",
  "created_at": "2024-02-10T15:17:35.176525Z",
  "data_removed": false,
  "error": null,
  "id": "rkqcqjlb5yfzubsedohlvv5jmi",
  "input": {
    "seed": 10,
    "prompt": "on a marble table",
    "style_image": "https://replicate.delivery/pbxt/KNc7eIC5UqBH5GxAUu3i5WWgQooBWg1WQmKlZyFczvaftVw5/flower.jpg",
    "guidance_scale": 7.5,
    "controlnet_type": "canny",
    "negative_prompt": "over-exposure, under-exposure, saturated, duplicate, out of frame, lowres, cropped, worst quality, low quality, jpeg artifacts, morbid, mutilated, ugly, bad anatomy, bad proportions, deformed, blurry",
    "condtioning_image": "https://replicate.delivery/pbxt/KNc7dtQmRYksrDn4eC1qGrtlBJIkHHmk4S7OSMT8UAYMHRul/kettle.jpg",
    "num_inference_steps": 25,
    "style_subject_category": "flower",
    "target_subject_category": "teapot"
  },
  "logs": "Using seed: 10\n  0%|          | 0/26 [00:00<?, ?it/s]\n  8%|▊         | 2/26 [00:00<00:01, 19.88it/s]\n 15%|█▌        | 4/26 [00:00<00:01, 18.13it/s]\n 23%|██▎       | 6/26 [00:00<00:01, 17.66it/s]\n 31%|███       | 8/26 [00:00<00:01, 17.46it/s]\n 38%|███▊      | 10/26 [00:00<00:00, 17.34it/s]\n 46%|████▌     | 12/26 [00:00<00:00, 17.29it/s]\n 54%|█████▍    | 14/26 [00:00<00:00, 17.27it/s]\n 62%|██████▏   | 16/26 [00:00<00:00, 17.23it/s]\n 69%|██████▉   | 18/26 [00:01<00:00, 17.18it/s]\n 77%|███████▋  | 20/26 [00:01<00:00, 17.16it/s]\n 85%|████████▍ | 22/26 [00:01<00:00, 17.17it/s]\n 92%|█████████▏| 24/26 [00:01<00:00, 17.16it/s]\n100%|██████████| 26/26 [00:01<00:00, 17.16it/s]\n100%|██████████| 26/26 [00:01<00:00, 17.33it/s]",
  "metrics": {
    "predict_time": 3.044941,
    "total_time": 3.11242
  },
  "output": "https://replicate.delivery/pbxt/grofXNTfdclmq0Ake6s2tiWsmNUClsXPhlqUJ3h3uoAisoqkA/out.png",
  "started_at": "2024-02-10T15:17:35.244004Z",
  "status": "succeeded",
  "urls": {
    "get": "https://api.replicate.com/v1/predictions/rkqcqjlb5yfzubsedohlvv5jmi",
    "cancel": "https://api.replicate.com/v1/predictions/rkqcqjlb5yfzubsedohlvv5jmi/cancel"
  },
  "version": "0072c227cdc7eea6c41411b54655b874faac1a7b8288386dc2a3c677c6faa403"
}

Generated in

3.0 seconds

Tweak it Share Report